Occurrence dataset for the subspecies of the American badger (Taxidea taxus berlandieri) in the north-central region of Mexico

The subspecies of American badger (Taxidea taxus berlandieri Baird, 1858), also called tlalcoyote (Figure 1), is distributed in north-central Mexico. However, its occurrence records are scarce and the few that exist are uncertain due to incorrect georeferencing or identification of the taxonomic unit. In view of this, we disgned a spatial sampling in part of the states of Coahuila de Zaragoza, Durango, Nuevo León, San Luis Potosí and Zacatecas. In this north-central protion of Mexico, we generated a grid of squares measuring 5 × 5 km over the entire study area using QGIS® 3.10 software. Subsequently, we excluded squares that included urban settlements, agricultural land, or water bodies in more than 30% of their extension; we also descarted squares located at an altitude over 2,250 meters above sea level. To perform this filtering, we used both the land use and vegetation chart of the INEGI [Instituto Nacional de Estadística, Geografía e Informática] (2018) and the Digital Elevation Model (DEM) downloaded from the USGS page [United States Geological Survey] (2019) as a basis. As result, we obtained 3,471 squares separated by at least 5 km. Then, through simple random sampling, 177 (≈5%) squares were selected, where we generated centroids to be used as sampling sites. In field work, between 2009 and 2015, at these 177 sites we traced a 10 × 100 m transect, where we searched for T. t. berlandieri signs (i.e., burrows and scratching posts). In this case, their burrows and scratching posts are easily observed and quantified, and there is no chance of mistaking them for burrows of other species (Long 1973; Merlin 1999). Also, we recorded possible sightings, as other studies (e.g., Merlin 1999; Elbroch 2003). As result, we only found 33 with signs of occurrence. Figure 1. Individual of tlalcoyote (Taxidea taxus Berlandieri). Photo obtained from Naturalista (2023) and uploaded by David Molina©. All rights reserved (CC BY-NC-ND). To increase the number of records, we included occurrence data from GBIF [Global Biodiversity Information Facility portal] (2022). We downloaded only the records that included coordinates and that their basis of registration was "preserved specimen". This, because they are correctly identified as specimens from biological collections (Maldonado et al. 2015). In addition, we only selected records for Mexico. Subsequently, we filtered the downloaded database, discarding records that were incorrectly georeferenced, with atypical and duplicate coordinates, as well as with low geospatial accuracy (e.g., less than three decimals of precision). We loaded the remaining data into the QGIS® software and performed a spatial filtering, where we excluded data that were outside the study area, located in unlikely areas (e.g., human settlements, bodies of water, agricultural areas) and with a distance of less than 5 km from the records obtained in the field. This gave a total of 10 records from the GBIF portal. Finally, we loaded the raster layers of elevation (Elev; INEGI 2007), normalized difference vegetation index (NDVI, USGS 2019) and the slope of the terrain into the software to extract the pixel values based on the GBIF records and those obtained in the field. With this, we generated a new global dataset to which we performed environmental filtering to find environmental outliers. We plotted the normality distribution of the data for each variable and the dispersion of the data among the variables. In this filtering, we conserve all records. Figure 2 shows the normality distribution of the records as a function of Elev. Figure 3 shows the dispersion of the data between Elev and NDVI. Figure 2. Normality distribution of T. t. berlandieri occurrence records as a function of the elevation variable (Elev). Figure 3. Scatter plot of T. t. berlandieri occurrence records as a function of elevation (Elev) and normalized difference vegetation index (NDVI). For the north-central region of Mexico, we present the global database (i.e., Tatabe_joint.csv), as well as the database that contains only the field evidence records (i.e., Tatabe_first_order.csv) and another one with the filtered GBIF records (i.e., Tatabe_GBIF.csv).美洲獾（American badger）的亚种贝氏美洲獾（Taxidea taxus berlandieri Baird, 1858），又名tlalcoyote（图1），分布于墨西哥中北部地区。然而，该亚种的出现记录稀缺，且现存记录因地理参照错误或分类单元鉴定有误，多数可信度存疑。有鉴于此，我们在科阿韦拉-萨拉戈萨州、杜兰戈州、新莱昂州、圣路易斯波托西州以及萨卡特卡斯州的部分区域设计了空间抽样方案。在墨西哥中北部的这一研究区域内，我们使用QGIS® 3.10软件生成了覆盖全研究区的5×5 km方格网格。随后，我们剔除了城镇定居点、农用地或水体占比超过30%的方格；同时剔除了海拔高于2250米的方格。为完成该筛选步骤，我们以墨西哥国家统计地理与信息研究所（Instituto Nacional de Estadística, Geografía e Informática, INEGI）2018年发布的土地利用与植被图，以及美国地质调查局（United States Geological Survey, USGS）2019年下载的数字高程模型（digital elevation model, DEM）作为依据。最终共得到3471个彼此间距至少5 km的方格。随后通过简单随机抽样，选取了177个（约5%）方格，并生成其质心作为样点位置。 2009年至2015年的野外调查中，我们在这177个样点设置了10×100 m的样线，用于搜寻贝氏美洲獾的活动痕迹（即洞穴与抓扒标记点）。该亚种的洞穴与抓扒标记点易于观测和计数，且不会与其他物种的洞穴混淆（Long 1973; Merlin 1999）。此外，我们还记录了可能的目击记录，参考了其他相关研究（如Merlin 1999; Elbroch 2003）的方法。最终仅在33个样点中发现了该亚种的活动痕迹。 图1. 贝氏美洲獾（Taxidea taxus berlandieri）个体。照片源自Naturalista（2023），由David Molina上传©。保留所有权利（CC BY-NC-ND）。 为增加出现记录的数量，我们纳入了全球生物多样性信息设施（Global Biodiversity Information Facility portal, GBIF）2022年的出现数据。我们仅下载包含坐标信息且记录依据为"馆藏标本（preserved specimen）"的记录，因为这类记录已被正确鉴定为生物馆藏标本（Maldonado等人，2015）。此外，我们仅选取墨西哥境内的记录。随后对下载的数据库进行筛选，剔除地理参照错误、坐标异常或重复、以及地理空间精度较低（如精度不足三位小数）的记录。 我们将剩余数据导入QGIS®软件并开展空间筛选，剔除研究区外、位于不适生区域（如城镇居民点、水体、农用地）以及与野外获取的记录间距小于5 km的数据。最终从GBIF平台共得到10条有效记录。随后，我们将海拔栅格图层（Elev；INEGI 2007）、归一化植被指数（normalized difference vegetation index, NDVI；USGS 2019）以及地形坡度图层导入软件，基于GBIF记录与野外获取的记录提取各栅格的像元值。据此生成了新的整合数据集，并对其开展环境筛选以识别环境异常值。我们绘制了各变量的数据正态分布以及变量间的数据离散程度图。本次筛选保留了所有记录。图2展示了以海拔（Elev）为变量的贝氏美洲獾出现记录的正态分布情况。图3展示了以海拔（Elev）与归一化植被指数（NDVI）为变量的贝氏美洲獾出现记录的数据离散程度散点图。 图2. 贝氏美洲獾（T. t. berlandieri）出现记录基于海拔变量（Elev）的正态分布情况。 图3. 贝氏美洲獾（T. t. berlandieri）出现记录基于海拔（Elev）与归一化植被指数（NDVI）的散点离散图。 针对墨西哥中北部区域，我们提供了整合数据集（即Tatabe_joint.csv）、仅包含野外调查痕迹记录的数据集（即Tatabe_first_order.csv），以及经筛选的GBIF记录数据集（即Tatabe_GBIF.csv）。